gusucode.com > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM源码程序 > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM\stprtool\svm\poaasvm.m
function poaaosvm(model,background) % POAASVM vizualizes One-Against-All SVM decision rule. % poaasvm(model,background) % % Input: % model [struct] model of classifier. % background [int] 0 - no, 1 - yes. % % Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac % (c) Czech Technical University Prague, http://cmp.felk.cvut.cz % Written Vojtech Franc (diploma thesis) 23.12.1999, 5.4.2000 % Modifications % 26-aug-2002, VF % 9-july-2002, VF % 19-sep-2001, V. Franc, comments changed. % 20-may-2001, V. Franc, new approach % 16-april-2001, V. Franc, created if nargin < 2, background = 0; end % points size POINTSSIZE=10; % grid for x-axis and y-axis GRIDX=150; GRIDY=150; epsilon=1e-5; if nargin < 1, error('Not enough input arguments.'); return; end ppatterns(model.trn_data,model.trn_labels,POINTSSIZE); hold on; V = axis; dx = (V(2)-V(1))/GRIDX; dy = (V(4)-V(3))/GRIDY; [X,Y] = meshgrid(V(1):dx:V(2),V(3):dy:V(4)); % make testing points tst_data=[reshape(X',1,prod(size(X)));reshape(Y',1,prod(size(Y)))]; % classify points D = zeros(model.num_classes,size(tst_data,2) ); for i=1:model.num_classes, [pred_labels,dfce] = svmclass2(tst_data,model.trn_data,... multi2dicho(model.trn_labels,i),... model.rule{i}.Alpha,model.rule{i}.bias,model.SVM.kernel,model.SVM.arg); D(i,:) = dfce; end pdiscrim( D, V(1):dx:V(2), V(3):dy:V(4),background ); if background, ppatterns(model.trn_data,'kx',POINTSSIZE); else ppatterns(model.trn_data,model.trn_labels,POINTSSIZE); end axis(V); hold off; return;